Streamlining Large-Scale Dataset Migrations with Background Coding Agents: A Practical Guide

Overview

Migrating thousands of datasets downstream to consumers is a monumental task. At Spotify, we reduced this pain by combining three powerful internal tools—Honk, Backstage, and Fleet Management—into a system of background coding agents. This tutorial walks you through building a similar solution to automate dataset migrations, improve reliability, and cut manual effort. By the end, you'll have a reusable framework that can handle migrations at scale.

Prerequisites

• Access to Honk – Ensure your environment supports Honk workflows. You'll need Honk CLI installed (honk version 2.3+).
• Backstage Setup – A deployed Backstage instance with the Software Catalog enabled. Admin rights to register components and templates.
• Fleet Management – A service to manage agent fleets (e.g., Kubernetes or Nomad). Assumes you can define agent pods and scaling policies.
• Dataset Metadata – A source of truth for dataset definitions (e.g., Hive Metastore, S3 inventories). We'll use a simple JSON registry here.
• Basic knowledge – Familiarity with YAML, Python (or similar scripting), and database migration patterns.

Step-by-Step Instructions

1. Define the Migration Workflow in Honk

Honk orchestrates background tasks. Create a workflow file dataset-migration.yml:

name: migrate-dataset
on:
  trigger:
    type: dataset_onboard
jobs:
  validate:
    steps:
      - run: python validate.py
  migrate:
    needs: [validate]
    steps:
      - run: python migrate.py --dataset '{{ input.dataset_name }}'
  notify:
    steps:
      - run: python notify_consumer.py

Register this workflow via Honk CLI: honk register workflow.yml.

2. Register Datasets in Backstage

Backstage catalogs each dataset as an entity. Add a YAML file per dataset:

apiVersion: backstage.io/v1alpha1
kind: Component
metadata:
  name: my-dataset
  annotations:
    honk/workflow: migrate-dataset
spec:
  type: dataset
  lifecycle: production
  owner: data-team

Import into Backstage: curl -X POST /api/catalog/import -d @my-dataset.yaml.

3. Configure Fleet Management Agents

Agents are long-running processes that listen for Honk events. Deploy a Fleet Manager (FM) agent pool:

# fleet-agent-config.json
{
  "agent_template": "fm-agent:latest",
  "replicas": 10,
  "env": {
    "HONK_API_URL": "http://honk.service"
  }
}

Use Fleet Management CLI: fm deploy --config fleet-agent-config.json. Each agent polls Honk for new migration jobs, executes the workflow, and reports status.

4. Implement Migration Scripts

Write migrate.py to handle actual data movement:

import argparse, json, boto3

def migrate(dataset):
    # Fetch dataset metadata from Backstage
    meta = json.load(open(f'{dataset}.meta.json'))
    source = meta['source']['s3']['bucket']
    target = meta['target']['s3']['bucket']
    s3 = boto3.client('s3')
    # Copy objects with transformation
    for obj in s3.list_objects(Bucket=source)['Contents']:
        key = obj['Key']
        s3.copy_object(Bucket=target, Key=key,
                       CopySource=f'{source}/{key}')
    # Update metadata in Backstage
    meta['status'] = 'migrated'
    with open(f'{dataset}.meta.json', 'w') as f:
        json.dump(meta, f)

if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('--dataset', required=True)
    args = parser.parse_args()
    migrate(args.dataset)

Similarly, write validate.py and notify_consumer.py following best practices.

5. Trigger a Migration Manually

Use Honk API to simulate a dataset onboarding event:

curl -X POST http://honk.api/events \
  -H "Content-Type: application/json" \
  -d '{"type":"dataset_onboard","payload":{"dataset_name":"my-dataset"}}'

The agent fleet picks up the event, runs the workflow, and updates Backstage. Check logs: honk workflow logs my-dataset.

6. Automate with Backstage Templates

Create a Backstage template to trigger migrations from the UI:

apiVersion: scaffolder.backstage.io/v1beta3
kind: Template
metadata:
  name: migrate-dataset-template
spec:
  parameters:
    - title: Dataset Name
      properties:
        name:
          type: string
  steps:
    - id: trigger
      name: Trigger Migration
      action: http:backstage:request
      input:
        method: POST
        url: 'http://honk.api/events'
        body: |
          {
            "type": "dataset_onboard",
            "payload": {"dataset_name": "${{ parameters.name }}"}
          }

Register the template in Backstage, and your team can migrate datasets with one click.

Common Mistakes

Ignoring Workflow Dependencies

Agents may run concurrently; without proper sequencing, data can get corrupted. Always use Honk's needs directive to order jobs.

Overlooking State Management

Agents are stateless by design. Store migration progress externally (e.g., in Backstage annotations or a database) to resume after failures.

Hardcoding Configuration

Environment-specific values (bucket names, endpoints) should be injected via fleet agent environment variables, not baked into code.

Neglecting Error Handling

Add retry logic and dead-letter queues. Honk supports retry_count and timeout in workflows—use them.

Failing to Notify Downstream

After migration, consumers need to update their pointers. Include a notification step (e.g., email, Slack, Backstage catalog update).

Summary

Background coding agents—powered by Honk orchestration, Backstage discovery, and Fleet Management scalability—automate hundreds of dataset migrations without human intervention. This guide showed how to define workflows, register datasets, deploy agent fleets, and trigger migrations. Avoid common pitfalls by managing state, dependencies, and notifications. Your downstream consumers will thank you.